Workflow Templates

How it works This workflow runs on a schedule to monitor HubSpot deals with upcoming contract expiry dates. It filters deals that are 30, 60, or 90 days away from expiration and processes each one individually. Based on the remaining days, it sends personalized email reminders to contacts via Gmail. It also notifies account managers in Slack and creates follow-up tasks in ClickUp for tracking. Step-by-step Schedule and filter expiring deals** Schedule Trigger – Runs the workflow at defined intervals. Get all deals – Fetches deals and contract expiry data from HubSpot. Filter Deals – Calculates days left and keeps only 30, 60, or 90-day expiries. Process deals and fetch contacts** Loop Over Deals – Iterates through each filtered deal. Fetch Associated Contact With Deal – Retrieves linked contact IDs via API. Get Contact Details – Pulls contact email and basic info from HubSpot. Route and send reminder emails** Switch – Routes deals based on days left (30, 60, 90). 30 day mail – Sends urgent renewal reminder via Gmail. 60 day mail – Sends friendly renewal notification email. 90 day mail – Sends early awareness email. Merge – Combines all email paths into a single output. Notify team and create follow-ups** Nofity Account Manager – Sends Slack alert with deal and contact details. Create Follow-up Task – Creates a ClickUp task for renewal tracking. Why use this? Prevent missed renewals with automated tracking and alerts Improve customer retention through timely communication Reduce manual CRM monitoring and follow-ups Keep teams aligned with Slack notifications and task creation Scale contract management without increasing workload

How it works: This workflow fetches sent campaign data from Brevo on a schedule, calculates key metrics (open rate, click rate, bounce rate), and stores results in Google Sheets. It then filters to a rolling 7-day window, runs an AI analysis to generate an executive summary with performance highlights and recommendations, and delivers a structured HTML report by email to stakeholders. Step-by-step: Data collection Schedule Trigger – Fires the workflow on your chosen day and time. HTTP Request (Brevo) – Fetches sent campaign data via the Brevo API. Transform Data – Calculates open rate, click rate, and bounce rate per campaign. Write to Google Sheets – Appends processed results to the historical database. Data preparation Read from Google Sheets – Retrieves the latest stored campaign records. Filter to 7-day window – Narrows data to the last 7 days for trend analysis. Aggregate Results – Summarises campaign performance across the window. AI analysis AI Summary Engine – Evaluates trends and generates an executive summary. LLM (Groq or alternative) – Provides the AI model for analysis. Format AI Output – Structures the summary for use in the report. Report delivery Build HTML Report – Compiles metrics, highlights, and recommendations into a styled email. Send via Gmail – Delivers the final report to stakeholder recipients. Why use this? Automates the full reporting lifecycle from data pull to inbox delivery. Surfaces top-performing campaigns and list health issues without manual review. Keeps a growing historical database for long-term trend tracking. Easily adjustable reporting window, thresholds, and notification channels. Works with any AI provider — swap Groq for any compatible LLM.

Introduction Automates scholarship tracking by scraping university sites, assessing eligibility via AI, and publishing results to WordPress or Slack. Eliminates manual searches for students, counselors, and education platforms, enabling scalable curation and timely notifications. How it Works Webhook triggers parallel scraping of NUS, NTU, SIT, SUTD → merge data → AI evaluates eligibility → aggregate qualified scholarships → generate summaries → post to WordPress/Slack → send email notifications with appeal options. Setup Steps Configure OpenAI credentials and eligibility prompt template Update HTTP requests with university URLs and selectors Add WordPress site URL and API credentials Create Slack webhook and notification channel Configure Gmail/SMTP for email notifications Workflow Webhook → Scrape 4 Universities (Parallel) → Merge Data → Prepare Context → AI Eligibility Check → Aggregate Results → Generate Summary → Check Status → Publish Slack/Email/WordPress → Handle Appeals Workflow Steps Scraping: Fetch scholarship pages from four universities simultaneously Merge: Combine data into a unified dataset AI Processing: Analyze eligibility criteria, deadlines against student profile Aggregation: Consolidate qualified scholarships with match scores Publishing: Post to WordPress, send Slack/email with results Appeals: Webhook handles rejection appeals with AI review Prerequisites OpenAI API key, WordPress site with REST API, Slack workspace with webhook, Gmail/SMTP credentials, student profile data (GPA, citizenship, major) Use Cases Counselors automating recommendations for 100+ students, financial aid offices aggregating departmental opportunities Customization Add universities (SMU, SUSS, international institutions), include government schemes (MOE, Edusave, Mendaki) Benefits Saves 10+ hours weekly per counselor, monitors 50+ scholarships automatically, provides AI eligibility matching (85%+ accuracy)

Introduction Automates Singapore COE price tracking, predicts trends using AI, and recommends optimal car purchase timing. Scrapes LTA data biweekly, analyzes historical trends, forecasts next 6 bidding rounds, and sends alerts when buying windows appear—saving time and identifying cost-saving opportunities. How it Works Biweekly trigger scrapes LTA COE data → processes historical trends → AI predicts 6-month prices → compares current vs forecast → generates buy/wait recommendations → alerts sent via Gmail or Telegram. Setup Steps Add NVIDIA/OpenAI API credentials in n8n Connect Google Sheets for data storage Authenticate Gmail/Telegram for notifications Schedule trigger for Wednesdays 8PM SGT Configure alert thresholds in conditional nodes Workflow Schedule Trigger → HTTP Request (Scrape LTA) → Data Processing → Google Sheets (Store) → AI Prediction → Analysis Engine → Conditional Logic → Gmail/Telegram Notification Workflow Steps Scraping: Extract COE prices from OneMotoring Processing: Calculate moving averages, volatility, seasonal trends Storage: Save to Google Sheets with timestamps Prediction: AI forecasts next 6 bidding rounds Analysis: Compare current vs predicted prices, generate recommendation Notification: Alerts via email/Telegram Prerequisites NVIDIA/OpenAI API key, Google account (Sheets), Gmail/Telegram for notifications, basic COE category knowledge Use Cases First-time buyers monitoring price dips, fleet managers timing bulk purchases Customization Add economic indicators, integrate car loan calculators, track parallel imported car prices Benefits Saves hours of manual monitoring, captures 10–15% price dips, provides data-driven purchase timing (potential $5K–$15K savings)

Reduce MTTR with context-aware AI severity analysis and automated SLA enforcement Know that feeling when a "low priority" ticket turns into a production fire? Or when your on-call rotation starts showing signs of serious burnout from alert overload? This workflow handles that problem. Two AI agents do the triage work—checking severity, validating against runbooks, triggering the right response. What This Workflow Does Incident comes in through webhook → two-agent analysis kicks off: Agent 1 (Incident Analyzer) checks the report against your Google Sheets runbook database. Looks for matching known issues, evaluates risk signals, assigns a confidence-scored severity (P1/P2/P3). Finally stops you from trusting "CRITICAL URGENT!!!" subject lines. Agent 2 (Response Planner) builds the action plan: what to do first, who needs to know, investigation steps, post-incident tasks. Like having your most experienced engineer review every single ticket. Then routing happens: P1 incidents** → PagerDuty goes off + war room gets created + 15-min SLA timer starts P2 incidents** → Gmail alert + you've got 1 hour to acknowledge P3 incidents** → Standard email notification Nobody responds in time? Auto-escalates to management. Everything logs to Google Sheets for the inevitable post-mortem. What Makes This Different | Feature | This Workflow | Typical AI Triage | |---------|--------------|-------------------| | Architecture | Two specialized agents (analyze + coordinate) | Single generic prompt | | Reliability | Multi-LLM fallback (Gemini → Groq) | Single model, fails if down | | SLA Enforcement | Auto-waits, checks, escalates autonomously | Sends alert, then done | | Learning | Feedback webhook improves accuracy over time | Static prompts forever | | Knowledge Source | Your runbooks (Google Sheets) | Generic templates | | War Room Creation | Automatic for P1 incidents | Manual | | Audit Trail | Every decision logged to Sheets | Often missing | How It Actually Works: Real Example Scenario: Your monitoring system detects database errors. Webhook receives this messy alert: { "title": "DB Connection Pool Exhausted", "description": "user-service reporting 503 errors", "severity": "P3", "service": "user-service" } Agent 1 (Incident Analyzer) reasoning: Checks Google Sheets runbook → finds entry: "Connection pool exhaustion typically P2 if customer-facing" Scans description for risk signals → detects "503 errors" = customer impact Cross-references service name → confirms user-service is customer-facing Decision: Override P3 → P2 (confidence score: 0.87) Reasoning logged: "Customer-facing service returning errors, matches known high-impact pattern from runbook" Agent 2 (Response Coordinator) builds the plan: Immediate actions:** "Check active DB connections via monitoring dashboard, restart service if pool usage >90%, verify connection pool configuration" Escalation tier:** "team" (not manager-level yet) SLA target:** 60 minutes War room needed:** No (P2 doesn't require it) Recommended assignee:** "Database team" (pulled from runbook escalation contact) Notification channels:** #incidents (not #incidents-critical) What happens next (autonomously): Slack alert posted to #incidents with full context 60-minute SLA timer starts automatically Workflow waits, then checks Google Sheets "Acknowledged By" column If still empty after 60 min → escalates to #engineering-leads with "SLA BREACH" tag Everything logged to both Incidents and AI_Audit_Log sheets Human feedback loop (optional but powerful): On-call engineer reviews the decision and submits: POST /incident-feedback { "incidentId": "INC-20260324-143022-a7f3", "feedback": "Correct severity upgrade - good catch", "correctSeverity": "P2" } → This correction gets logged to AI_Audit_Log. Over time, Agent 1 learns which patterns justify severity overrides. Key Benefits Stop manual triage:** What took your on-call engineer 5-10 minutes now takes 3 seconds. Agent 1 checks the runbook, Agent 2 builds the response plan. Severity validation = fewer false alarms:** The workflow cross-checks reported severity against runbook patterns and risk signals. That "P1 URGENT" email from marketing? Gets downgraded to P3 automatically. SLAs enforce themselves:** P1 gets 15 minutes. P2 gets 60. Timers run autonomously. If nobody acknowledges, management gets paged. No more "I forgot to check Slack." Uses YOUR runbooks, not generic templates:** Agent 1 pulls context from your Google Sheets runbook database — known issues, escalation contacts, SLA targets. It knows your systems. Multi-LLM fallback = 99.9% uptime:** Primary: Gemini 2.0. Fallback: Groq. Each agent retries 3x with 5-sec intervals. Basically always works. Self-improving feedback loop:** Engineers can submit corrections via /incident-feedback webhook. The workflow logs every decision + human feedback to AI_Audit_Log. Track accuracy over time, identify patterns where AI needs tuning. Complete audit trail:** Every incident, every AI decision, every escalation — all in Google Sheets. Perfect for post-mortems and compliance. Required APIs & Credentials Google Gemini API** (main LLM, free tier is fine) Groq API** (backup LLM, also has free tier) Google Sheets** (stores runbooks and audit trail) Gmail** (handles P2/P3 notifications) Slack OAuth2 API** (creates war rooms) PagerDuty** (P1 alerts—optional, you can just use Slack/Gmail) Setup Complexity This is not a 5-minute setup. You'll need: Google Sheets structure: 3 tabs: Runbooks, Incidents, AI_Audit_Log Pre-populated runbook data (services, known issues, escalation contacts) Slack configuration: 4 channels: #incidents-critical, #incidents, #management-escalation, #engineering-leads Slack OAuth2 with bot permissions Estimated setup time: 30-45 minutes Quick start option: Begin with just Slack + Google Sheets. Add PagerDuty later. Who This Is For DevOps engineers done being the human incident router SRE teams drowning in alert fatigue IT ops managers who need real accountability Security analysts triaging at high volume Platform engineers trying to automate the boring stuff

This workflow acts as your personal inbox assistant. It automatically filters, classifies, and responds to incoming emails using AI, saving you from manually sorting through leads or inquiries 24/7. 👥 Who’s it for Freelancers & Consultants** handling their own sales pipeline. Sales Professionals** who need to book meetings instantly. Small Business Owners** who want to automate customer support or lead triage. Agencies** managing inbound inquiries for multiple clients. ⚙️ How it works This workflow monitors your Gmail inbox and processes emails in three main stages: Filtering: It first checks if the sender is on your "Whitelist" (a Google Sheet). It also ignores automated calendar replies (like "Accepted" or "Declined" notifications) to prevent loops. AI Analysis: OpenAI (GPT-4) reads the email body to understand the sender's intent. Action: Based on the intent, it takes one of three paths: Schedule Meeting: If the lead wants to meet, it creates a Google Calendar event, sends a confirmation email with the link, and notifies you on Telegram. Auto Reply: If the lead declines or isn't interested, it sends a polite, context-aware "thank you" email. Needs Review: If the email is unclear, it waits (configurable delay) and sends a gentle follow-up email to re-engage them. 📋 Requirements n8n** (Self-hosted or Cloud) Gmail Account** (Connected via OAuth2) Google Sheets** (For the whitelist) Google Calendar** (For booking meetings) OpenAI API Key** (GPT-4o-mini or similar model) Telegram** (Optional, for notifications) 🛠️ How to set up Prepare the Whitelist: Create a Google Sheet with three columns: email, first_name, and company. Add the email addresses you want the bot to respond to. Configure Credentials: Connect your Google (Gmail, Sheets, Calendar) and OpenAI accounts in the workflow credentials settings. Link the Sheet: In the "Get row(s) in sheet" node, select your whitelist spreadsheet. Set the Model: Check the "Message a model" nodes to ensure your OpenAI model (e.g., gpt-4o-mini) is selected. Telegram (Optional): If you want notifications, create a bot with @BotFather and add your Chat ID/Credentials. If not, you can disable/remove the Telegram nodes. 🎨 How to customize the workflow Adjust the Delay:* The *"Wait"* node is currently set to *minutes for testing. Change this to 3 Days (or your preferred duration) for a real-world scenario. Brand Your Emails:* Open the *Code** nodes (e.g., "Personalize AI Reply"). You will see HTML code inside. Update the senderName, senderEmail, and footer text to match your brand identity. Refine AI Prompts:* You can modify the system prompt in the *"Message a model"** node to change the AI's tone (e.g., make it more formal or casual). 🧑‍💻 Creator Information Developed by: Adem Tasin 🌐 Website: ademtasin.com 💼 LinkedIn: Adem Tasin

Overview This workflow is designed to monitor the Top 5 cryptocurrencies in real-time, calculate trading signals (BUY, SELL, HOLD), and send human-readable alerts through multiple channels. It integrates data fetching, signal processing, AI-generated insights, and multi-channel notifications to provide a professional-grade crypto monitoring solution. Setup Schedule the trigger Fetch real-time coin data (CoinGecko, Binance API) Filter only required fields Check each data from loop Add the logic for minimum percentage comparison Use AI for analysis enhanced insights Send the notification only if signal is 'SELL' or 'BUY' Key Features Real-Time Crypto Monitoring: Continuously evaluates the top 5 cryptocurrencies for trading signals. Dynamic Signal Calculation: Generates BUY, SELL, HOLD signals based on 24h price change. If price changed below or above 2% the dynamic signal will assign to dedicated coin. Signal Change Alerts: Sends notifications only when meaningful changes occur. Human-Readable Messaging: Converts numeric signals into readable alerts. AI Insights: Provides explanations or trading advice via OpenAI. Multi-Channel Delivery: Supports WhatsApp, Telegram, and Email. Looped Processing: Each coin is processed independently for accurate alerting. Wait / Delay Node: Prevents API rate limit issues and controls alert flow. Requirements OpenAI API WhatsApp API Telegram API SMTP Credentials or Gmail Credentials.

Description This workflow helps you find and evaluate job opportunities automatically, without spending hours searching and comparing roles. It uses your resume to look for relevant jobs on LinkedIn, checks how well each role matches your profile, and organises everything neatly in Google Sheets so you can focus on applying to the best opportunities. How it works On a schedule, the workflow downloads your resume from Google Drive and analyses it to understand your skills and experience. Based on this, it creates LinkedIn job searches and pulls in recent job listings. Each job is then reviewed using AI to compare the job description with your resume, produce a match score, suggest resume improvements, and generate a tailored cover letter. All results are saved to Google Sheets, and you’re notified by email when the run finishes. How to use Make a copy of the Google Sheets template and keep it for your own job tracking. Upload your resume (PDF) to Google Drive. Connect your Google Drive, Google Sheets, Gmail, and AI credentials in n8n. Update the Config node with your preferences (remote work, Easy Apply, job limit). Paste your copied Google Sheet IDs into the workflow. Turn on the Schedule Trigger and activate the workflow. Requirements Google Drive account for storing your resume Google Sheets account for tracking results Gmail account for notifications AI model access (Google Gemini or similar) n8n (cloud or self-hosted) Customising this workflow You can easily adapt this workflow to suit your goals. Change the job limits, locations, or remote preferences in the Config node. Update the AI prompts to target different roles or industries, or extend the workflow to send results to tools like Notion, a CRM, or your own application tracker. Good to know This workflow is designed to help you screen and prepare for jobs, not to apply automatically. Match scores are a guide, not a guarantee, so it’s always worth reviewing roles manually. Also, since LinkedIn pages can change over time, you may occasionally need to update HTML selectors to keep things running smoothly.

This n8n workflow automates job discovery by scanning company career pages, extracting open positions using AI, filtering them by department, and sending real-time alerts via Slack and email. It is ideal for monitoring targeted job roles (such as Engineering) across multiple companies without manual checking. Use Cases Targeted Job Monitoring: Automatically track new job postings for a specific department or role. Faster Job Alerts: Receive instant Slack and email notifications when relevant positions are found. Multi-Company Career Tracking: Monitor multiple company career pages from a single Airtable base. Reduced Noise: Filter out irrelevant roles and avoid empty or misleading notifications. Good to Know The workflow runs on a schedule and processes career pages stored in Airtable. Jobs are processed in batches with a delay node to avoid rate limits or scraping issues. Google Gemini is used for intelligent job extraction and filtering, which may incur API costs. If no relevant jobs are found, the workflow safely returns “No matching positions found” to prevent false alerts. Some Gemini models may be geo-restricted depending on your region. How it Works Step 1: Job Source & Scheduling A Schedule Trigger starts the workflow and defines the job category to monitor (e.g., Engineering). Airtable is queried to fetch all company career page URLs. Step 2: Scraping & Extraction Each career page is scraped using Decodo. Google Gemini analyzes the raw page content and extracts job titles with application URLs while ignoring navigation and non-job content. Step 3: Data Cleaning & Structuring A JavaScript code node cleans the AI output, removes noise (e.g., “No open positions”), and converts results into structured job items. Step 4: AI-Based Filtering A second AI Agent compares extracted jobs against the target department and keeps only relevant roles. Step 5: Notifications Matching jobs are sent instantly to Slack and email. How to Use Airtable Credentials: Connect Airtable and store career page URLs in the table. Google Gemini Credentials: Add your Gemini API key for AI extraction and filtering. Slack Credentials: Select a user or channel to receive job alerts. Gmail Credentials: Configure Gmail to receive job notification emails. Schedule Setup: Adjust the trigger interval based on how often you want job checks. Activate Workflow: Enable the workflow to start automated job monitoring. Requirements n8n instance (self-hosted or cloud) Airtable base with company career page URLs Google Gemini API key Slack workspace Gmail account for email notifications

How it works This workflow automatically manages every new Calendly booking from start to finish. When a prospect books a meeting, it captures all details, syncs everything to HubSpot, creates a prep task for the sales rep, sends confirmation and reminder emails, and notifies the team — all without any manual effort. Step-by-step Trigger & format** Calendly — New Booking – Listens for new invitee.created events when a prospect books a meeting. Format Booking Data – Extracts and normalizes all booking details including name, email, company, phone, meeting time, join URL, reschedule and cancel links, and computes reminder timestamps. Logging** Google Sheets — Log Booking – Appends all booking details including name, email, company, event type, meeting time, and join URL to a Google Sheets tracker. CRM sync** HubSpot — Search Contact by Email – Searches HubSpot to check if the prospect already exists by email. IF — Contact Exists in HubSpot? – Routes to update or create based on whether a matching contact is found. Update HubSpot Contact – Updates the existing contact with the latest name, phone, company, and lead source. Create HubSpot Contact – Creates a new HubSpot contact with all prospect details if none exists. Set — Contact ID – Normalizes the contact ID from either branch so all downstream nodes reference it consistently. Calendar & deal creation** Google Calendar — Create Rep Event – Creates a 30-minute meeting event on the sales rep's Google Calendar with join URL, prospect details, and reschedule/cancel links. HubSpot — Get Owner ID – Fetches the HubSpot owner to assign the deal to the correct sales rep. HubSpot — Create a Deal – Creates a new deal in the appointmentscheduled stage linked to the contact, with meeting details and next steps. Preparation & confirmation** ClickUp — Create Prep Task – Creates a pre-call research task in ClickUp with a full checklist covering LinkedIn research, company background, discovery questions, and competitor analysis. Due 2 hours before the meeting. Gmail — Send Confirmation – Sends a polished HTML confirmation email to the prospect with meeting details, join button, and reschedule/cancel options. Team notification & CRM logging** HubSpot Log Note – Logs a full activity note in HubSpot linked to both the contact and the deal, including all meeting details and the ClickUp prep task link. Slack — Notify Sales Channel – Posts a booking alert to the sales Slack channel with prospect info, meeting time, join URL, and confirmation of all actions taken. Automated reminders** Wait — Until 24h Before Meeting – Pauses execution until exactly 24 hours before the scheduled meeting. Gmail — Send 24h Reminder – Sends an HTML reminder email with meeting details, join link, and a pre-call checklist. Wait — Until 1h Before Meeting – Pauses execution until exactly 1 hour before the meeting. Gmail — Send 1h Reminder – Sends a final HTML reminder email with a prominent join button and last-minute tips. Why use this? Eliminates all manual admin after a Calendly booking by instantly syncing data across HubSpot, Google Sheets, and Google Calendar Auto-creates or updates HubSpot contacts and deals so no lead ever falls through the cracks Gives sales reps a structured ClickUp prep task with a research checklist before every call Keeps prospects engaged and informed with a confirmation email plus automated 24h and 1h reminders Notifies the entire sales team in Slack the moment a new meeting is booked

How it works This workflow automatically handles every resolved Jira bug by verifying the fix, notifying the customer, updating HubSpot, commenting on the Jira issue, alerting the team on Slack, and logging everything to Google Sheets — all without any manual effort. If customer contact details are missing, it routes to a manual follow-up alert instead. Step-by-step Trigger & filter** Jira Trigger – Listens for jira:issue_updated events on your Jira project. Filter: Bug Resolved? – Checks that the issue type is Bug, the status moved to Done, and the changelog contains a status change before proceeding. Normalize & deduplicate** Normalize & Enrich Payload – Extracts and enriches all issue data including summary, priority, components, fix versions, labels, sprint, assignee, reporter, resolution comment, customer email, days open, and a direct Jira issue URL. Deduplication Check – Uses workflow static data to check if this issue key has already been processed, preventing duplicate notifications. Already Processed? – Stops the workflow if the issue was previously handled; continues only for first-time resolutions. Customer contact check** Has Customer Email? – Routes to the full notification path if a customer email is found, or to the manual follow-up path if not. Data enrichment (parallel)** Get Jira Issue Details – Fetches the full Jira issue including comments, attachments, and worklogs to extract the latest resolution comment. Search HubSpot Contact – Searches HubSpot by customer email to retrieve existing contact details including name and company. Merge Jira + HubSpot Data – Combines both parallel fetch results into a single data object. Merge Data & Build Templates – Builds the complete HTML customer email, HubSpot note body, and email subject line using all enriched data. Notifications & CRM updates** Send Gmail to Customer – Sends a polished HTML resolution email to the customer with issue summary, fix details, resolution notes, assignee, days to resolve, and a link to the Jira issue. Add Jira Comment – Posts a resolution summary comment directly on the Jira issue confirming the customer was notified. Create/Update HubSpot Contact – Creates or updates the HubSpot contact record with the customer's details. Log HubSpot Note – Logs a full resolution note on the HubSpot contact linked to their record. Slack Team Notification – Posts a detailed resolution summary to the team Slack channel including issue details, assignee, days open, HubSpot status, and resolution notes. Log to Google Sheets – Appends or updates the resolution record in Google Sheets with issue key, priority, component, fix version, customer details, assignee, days open, sprint, HubSpot status, and email status. Missing email fallback** Log: No Email Found – Flags the issue for manual follow-up and logs a warning when no customer email is available on the Jira ticket. Alert: Manual Follow-Up – Sends a Slack alert to the team requesting manual customer outreach for issues where no email could be found. Why use this? Instantly notifies customers the moment a bug is resolved with a professional HTML email including full resolution details Built-in deduplication prevents customers from receiving the same resolution notification twice Automatically handles missing contact info by routing to a manual follow-up Slack alert so no resolved issue goes uncommunicated Keeps HubSpot fully in sync with resolution notes logged directly on the customer contact record Gives the engineering team a real-time Slack summary and a permanent Google Sheets audit trail of every resolved bug

AI-Powered Lead Qualification & Enrichment Pipeline 🎯 Who is this for? This template is perfect for: Marketing Teams** looking to automatically qualify inbound leads from campaigns Sales Teams** wanting to prioritize high-value prospects instantly Agencies** offering lead qualification as a service to clients SaaS Companies** routing trial signups to appropriate nurture sequences B2B Service Providers** scoring and enriching leads from multiple sources 💡 What problem does it solve? Manual lead qualification is slow, inconsistent, and expensive. Sales teams waste hours on unqualified leads while hot prospects go cold. This workflow: Eliminates manual research** - Automatically enriches company data via LinkedIn Scores leads instantly** - AI analyzes 15+ data points to score 0-100 Routes intelligently** - Hot leads get instant alerts, warm leads enter nurture Personalizes outreach** - AI generates custom emails based on company context ⚡ What this workflow does 1. Lead Capture & Validation Captures leads via built-in n8n Form (embeddable on any website) Validates email format and detects business vs personal emails Normalizes data from various field naming conventions 2. Company Enrichment via Apify Uses Google Search to find company's LinkedIn profile Scrapes LinkedIn for industry, size, description, specialties, and more Gracefully skips enrichment for personal emails (Gmail, Yahoo, etc.) 3. AI Lead Qualification (GPT-4.1) Scores leads 0-100 based on buying signals Assigns tier: Hot (80+), Warm (60-79), Cold (40-59), Disqualified (<40) Identifies buyer persona (Decision Maker, Influencer, Champion, etc.) Generates personalized talking points and risk factors 4. Intelligent Routing & Actions Hot Leads**: Instant Slack alert + AI-generated personalized email + HubSpot contact Warm Leads**: Slack notification for nurture sequence Cold Leads**: Logged for future reference All Leads**: Recorded to Google Sheets with full qualification data 🔧 Setup Required Credentials | Service | Purpose | |---------|---------| | OpenAI | AI qualification & email generation | | Apify | Google Search + LinkedIn scraping | Optional Credentials | Service | Purpose | |---------|---------| | Slack | Lead alerts and notifications | | HubSpot | CRM contact creation | | Gmail | Sending personalized emails | | Google Sheets | Lead database logging | Apify Setup Create account at apify.com Get API token from Settings → Integrations Open the Apify HTTP nodes and replace YOUR_API_KEY with the API token obtained in the above step Apify Actors Used Google Search Scraper PPR** (Actor ID: G9PR1B1upfS0mRvp0) - ~$0.004/search LinkedIn Company Scraper PPR** (Actor ID: G9y3V8J1hXYJTf1Ho) - ~$0.02/company Total cost: ~$0.02-0.03 per enriched lead 📊 Lead Scoring Criteria | Score | Tier | What it means | |-------|------|---------------| | 80-100 | 🔥 Hot | Strong buying signals, budget confirmed, urgent timeline | | 60-79 | 🌡️ Warm | Good fit, some buying signals, needs nurturing | | 40-59 | ❄️ Cold | Potential fit but unclear intent | | 0-39 | ⛔ Disqualified | Poor fit, spam, or invalid | 🎨 Customization Modify Form Fields Edit the "Lead Capture Form" node to add/remove fields for your use case. Adjust AI Scoring Edit the system prompt in "AI Lead Qualification" to customize: Score thresholds for your industry Buyer persona definitions Custom qualification criteria Add Integrations Easily extend with: Pipedrive, Salesforce, or other CRMs Email sequences (Mailchimp, ActiveCampaign) SMS notifications (Twilio) Calendar booking (Calendly) 📈 Example Output { "qualification": { "score": 85, "tier": "Hot", "buyerPersona": "Decision Maker", "urgencyLevel": "High" }, "insights": { "keyInsights": [ "VP-level with direct budget authority", "Company in growth phase (51-200 employees)", "Industry aligned with our ICP" ], "talkingPoints": [ "Reference their sustainability focus", "Highlight ROI for mid-market companies" ] } } 🙋 Need Help? Check the sticky notes in the workflow for section-by-section guidance Ensure Apify credentials are properly configured Test with a business email (not Gmail/Yahoo) to see full enrichment Created by Agentical AI - AI Automation Agency specializing in workflow automation and AI solutions.